US6629072B1 - Method of an arrangement for speech recognition with speech velocity adaptation - Google Patents

Method of an arrangement for speech recognition with speech velocity adaptation Download PDF

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Publication number
US6629072B1
US6629072B1 US09/649,675 US64967500A US6629072B1 US 6629072 B1 US6629072 B1 US 6629072B1 US 64967500 A US64967500 A US 64967500A US 6629072 B1 US6629072 B1 US 6629072B1
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Prior art keywords
speech
velocity
recognition
speech velocity
user
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US09/649,675
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Eric Thelen
Heribert Wutte
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Nuance Communications Austria GmbH
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Koninklijke Philips Electronics NV
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/065—Adaptation
    • G10L15/07—Adaptation to the speaker
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/221—Announcement of recognition results

Definitions

  • the invention relates to a method of and an arrangement for speech recognition.
  • Speech recognition For the execution of speech recognition it is necessary for a user to supply respective speech utterances to a speech recognizer. There is a plurality of criteria for this, which influence the quality of the recognition result produced from the speech utterance. A user is often not aware of the criterions of such a speech recognition device. Only the experienced user of a speech recognition device is successful in keeping the error rate in the recognition process so low that an acceptable result is achieved. Speech recognition devices have been developed such that also different speakers can produce speech utterances, which are then recognized by the speech recognition system. Such speech recognizers are denoted as speaker-independent speech recognition systems.
  • WO 87/07460 describes a telephone-based speech recognition system, in which the speech recognizer informs a user that no appropriate word was found in the vocabulary. The user is requested to repeat the speech utterance. When the speech recognition system is supplied with a too low-voiced or disturbed speech utterance, the user of the speech recognition system is requested to speak into the microphone at a higher voice.
  • each speech recognizer is based on an acoustic model, which in turn is based on an average speech velocity, is not taken into account.
  • a deviation of the user's speech velocity from the average speech velocity of the acoustic model considerably increases the error rate during the recognition process.
  • the object is achieved in that the speech velocity is measured, which the user is informed of.
  • a user For executing speech recognition, a user produces a speech utterance with an appropriate velocity.
  • Acoustic speech models which are based on an average velocity, are used for the recognition process. It is necessary to make an adaptation for a deviating speech velocity. With smaller deviations of the speech velocity from the average speech velocity of the acoustic model, an adaptation is possible, but leads to a degraded evaluation of hypotheses in the recognition process as a result of the time distortion resulting from the adaptation. With larger deviations from the average speech velocity, an adaptation is no longer possible, because the models cannot be run through with optionally high velocity. Furthermore, when most users speak fast, they often tend to swallow short words or word endings. Such errors cannot be reliably recognized by the speech recognition system.
  • the user's speech velocity is measured and the user is informed thereof via an output means.
  • the user is then persuaded to stick to an optimized speech velocity, which is oriented to the average speech velocity of the speech model.
  • Output means are, for example, LEDs for which a respective color (green) shows an acceptable speech velocity and another color (red) shows an unacceptable deviation.
  • Another possibility is the display of a number value by which the user is informed of the range in which this number value is to lie. With an exclusively audio-based communication, the user is informed by means of a warning signal that the speech velocity lies outside an acceptable range.
  • the measured speech velocity can advantageously also be applied to the speech recognizer as a confidence measure or for controlling the search process.
  • the speech recognizer is then informed of a measure according to which the speech recognizer can decide whether the speech velocity lies within respective limits, or whether a too high speech velocity is to be taken into account during the recognition process. The same holds for a too low speech velocity.
  • the speech velocity is determined by means of a suitable measure.
  • a speech recognition system is to be trained before it can perform a recognition. Therefore, it is important to take the speech velocity into account and announce this to the user already during the training.
  • a measure for the speech velocity is, for example, the number of spoken and also recognized words per time unit. However, more accurate is the measurement of the recognized phonemes per frame where the frame is considered to be a predefined time interval.
  • the announcement whether the speech velocity lies in the acceptable range may be linked with a transgression of an experimentally determined threshold value. Consequently, the user is then only informed when the speech velocity is too high, so that he is not distracted by the information—speech velocity lies in the acceptable range.
  • the threshold value may also be determined during the recognition process in that respective measures are transgressed or fallen short of during the recognition process.
  • a particular advantage of this invention is obtained from the learning process, which a user is to undergo.
  • the user makes a great effort to attain a high efficiency when using a speech recognition system. Since his speech velocity is displayed relative to the average speech velocity of the acoustic model, he consequently learns to adapt his speech velocity and thereby achieves a low error rate.
  • the object of the invention is achieved by a speech recognition device in which a measuring unit determines a speech velocity and informs the user thereof by means of an output unit.
  • FIG. 1 shows a speech recognition device.
  • the speech utterances are produced by a user or speaker and fed to a microphone 6 .
  • These analog speech data are applied to an input unit 5 , which performs a digitization of the speech data.
  • These digital speech data are then applied to the speech recognizer 1 .
  • There the speech recognition process is carried out.
  • the measuring unit 2 is supplied with the recognized phonemes and/or words. By means of the recognized phonemes and/or words, the speech velocity is determined in the measuring unit 2 .
  • the measuring unit 2 is connected to the output unit 3 and the speech recognizer 1 .
  • the measured speech velocity is applied to the output unit 3 and to the speech recognizer 1 as the case may be.
  • the speech recognizer 1 applies the recognition result, for example, to an interface unit 4 for a text-processing program, which shows the recognized words on a monitor.
  • An acoustic model is available to the speech recognizer 1 for the recognition result to be generated.
  • This acoustic model is based on an average speech velocity. This average speech velocity is compared with the measured speech velocity either in the speech recognizer 1 , or directly applied by the speech recognizer 1 to the output unit 3 for a direct comparison with the measured speech velocity in the output unit 3 .
  • a respective time unit is used as a base in the measuring unit.
  • phonemes are measured per time unit, phonemes are counted per frame and with words are counted per second.
  • the type of measurement used for measuring the speech velocity depends on the application.

Abstract

With a method of and an arrangement for speech recognition a measurement of the speech velocity rate is carried out in a measuring unit (2) so as to reduce the error rate of the recognition result, which speech velocity is announced to the speaker via an output unit (3) and warning is given if the velocity is out of speech recognition adaptation range.

Description

BACKGROUND OF THE INVENTION
The invention relates to a method of and an arrangement for speech recognition.
For the execution of speech recognition it is necessary for a user to supply respective speech utterances to a speech recognizer. There is a plurality of criteria for this, which influence the quality of the recognition result produced from the speech utterance. A user is often not aware of the criterions of such a speech recognition device. Only the experienced user of a speech recognition device is successful in keeping the error rate in the recognition process so low that an acceptable result is achieved. Speech recognition devices have been developed such that also different speakers can produce speech utterances, which are then recognized by the speech recognition system. Such speech recognizers are denoted as speaker-independent speech recognition systems.
WO 87/07460 describes a telephone-based speech recognition system, in which the speech recognizer informs a user that no appropriate word was found in the vocabulary. The user is requested to repeat the speech utterance. When the speech recognition system is supplied with a too low-voiced or disturbed speech utterance, the user of the speech recognition system is requested to speak into the microphone at a higher voice.
However, the fact that each speech recognizer is based on an acoustic model, which in turn is based on an average speech velocity, is not taken into account. A deviation of the user's speech velocity from the average speech velocity of the acoustic model considerably increases the error rate during the recognition process.
SUMMARY OF THE INVENTION
It is an object of the invention to provide a method and a device in which the error rate during the recognition process is reduced.
The object is achieved in that the speech velocity is measured, which the user is informed of.
For executing speech recognition, a user produces a speech utterance with an appropriate velocity. Acoustic speech models, which are based on an average velocity, are used for the recognition process. It is necessary to make an adaptation for a deviating speech velocity. With smaller deviations of the speech velocity from the average speech velocity of the acoustic model, an adaptation is possible, but leads to a degraded evaluation of hypotheses in the recognition process as a result of the time distortion resulting from the adaptation. With larger deviations from the average speech velocity, an adaptation is no longer possible, because the models cannot be run through with optionally high velocity. Furthermore, when most users speak fast, they often tend to swallow short words or word endings. Such errors cannot be reliably recognized by the speech recognition system. Whereas an adaptation is possible to a certain extent, an avoidance of pronunciation inadequacies with many possible users is only possible in the form of a reduction of the pronounciation inadequacies. The lacking words or words not fully pronounced can in all cases be inferred from the context.
Therefore, the user's speech velocity is measured and the user is informed thereof via an output means. The user is then persuaded to stick to an optimized speech velocity, which is oriented to the average speech velocity of the speech model. Output means are, for example, LEDs for which a respective color (green) shows an acceptable speech velocity and another color (red) shows an unacceptable deviation. Another possibility is the display of a number value by which the user is informed of the range in which this number value is to lie. With an exclusively audio-based communication, the user is informed by means of a warning signal that the speech velocity lies outside an acceptable range.
As a result, a lower error rate is advantageously achieved during the recognition process.
The measured speech velocity can advantageously also be applied to the speech recognizer as a confidence measure or for controlling the search process. The speech recognizer is then informed of a measure according to which the speech recognizer can decide whether the speech velocity lies within respective limits, or whether a too high speech velocity is to be taken into account during the recognition process. The same holds for a too low speech velocity.
During the recognition the speech velocity is determined by means of a suitable measure. A speech recognition system is to be trained before it can perform a recognition. Therefore, it is important to take the speech velocity into account and announce this to the user already during the training.
A measure for the speech velocity is, for example, the number of spoken and also recognized words per time unit. However, more accurate is the measurement of the recognized phonemes per frame where the frame is considered to be a predefined time interval.
The announcement whether the speech velocity lies in the acceptable range may be linked with a transgression of an experimentally determined threshold value. Consequently, the user is then only informed when the speech velocity is too high, so that he is not distracted by the information—speech velocity lies in the acceptable range.
The threshold value may also be determined during the recognition process in that respective measures are transgressed or fallen short of during the recognition process.
A particular advantage of this invention is obtained from the learning process, which a user is to undergo. The user makes a great effort to attain a high efficiency when using a speech recognition system. Since his speech velocity is displayed relative to the average speech velocity of the acoustic model, he consequently learns to adapt his speech velocity and thereby achieves a low error rate.
The object of the invention is achieved by a speech recognition device in which a measuring unit determines a speech velocity and informs the user thereof by means of an output unit.
BRIEF DESCRIPTION OF THE DRAWINGS
An example of embodiment of the invention will be further explained in the following with reference to the drawing.
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 shows a speech recognition device. The speech utterances are produced by a user or speaker and fed to a microphone 6. These analog speech data are applied to an input unit 5, which performs a digitization of the speech data. These digital speech data are then applied to the speech recognizer 1. There the speech recognition process is carried out. To determine the speech velocity, the measuring unit 2 is supplied with the recognized phonemes and/or words. By means of the recognized phonemes and/or words, the speech velocity is determined in the measuring unit 2. The measuring unit 2 is connected to the output unit 3 and the speech recognizer 1. The measured speech velocity is applied to the output unit 3 and to the speech recognizer 1 as the case may be. The speech recognizer 1 applies the recognition result, for example, to an interface unit 4 for a text-processing program, which shows the recognized words on a monitor.
An acoustic model is available to the speech recognizer 1 for the recognition result to be generated. This acoustic model is based on an average speech velocity. This average speech velocity is compared with the measured speech velocity either in the speech recognizer 1, or directly applied by the speech recognizer 1 to the output unit 3 for a direct comparison with the measured speech velocity in the output unit 3.
For the measurement of the speech velocity, a respective time unit is used as a base in the measuring unit. When phonemes are measured per time unit, phonemes are counted per frame and with words are counted per second. The type of measurement used for measuring the speech velocity depends on the application.

Claims (11)

What is claimed is:
1. A method of speech recognition characterized in that
a speech velocity is measured which is announced to the speaker.
2. A method as claimed in claim 1, characterized in that
the measured speech velocity is fed to the speech recognizer (1).
3. A method as claimed in claim 1, characterized in that
the speech velocity is determined by means of a measuring unit (2) during the recognition and/or training.
4. A method as claimed in claim 1, characterized in that
recognized phonemes and/or words are measured per predefinable time interval.
5. A method as claimed in claim 1, characterized in that
the speech velocity is shown as a function of a threshold value.
6. A method as claimed in claim 5, characterized in that
the threshold value is determined as a function of the error rate.
7. A method as claimed in claim 1, characterized in that
the speech velocity is continuously shown to the user.
8. The method as claimed in claim 1, wherein the providing step includes informing the speaker of the speech velocity.
9. A speech recognition device, characterized in that
a measuring unit (2) determines a speech velocity, determines whether, based on the measured speech velocity, speech recognition adaptation can be made, and informs the speaker thereof by means of an output unit (3).
10. A device as claimed in claim 9, characterized in that
the output unit (3) shows a range of the speech velocity by means of colors.
11. A device as claimed in claim 9, characterized in that
a transgression of the speech velocity is indicated by means of an audio output.
US09/649,675 1999-08-30 2000-08-28 Method of an arrangement for speech recognition with speech velocity adaptation Expired - Lifetime US6629072B1 (en)

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US7167544B1 (en) * 1999-11-25 2007-01-23 Siemens Aktiengesellschaft Telecommunication system with error messages corresponding to speech recognition errors
US20070192101A1 (en) * 2005-02-04 2007-08-16 Keith Braho Methods and systems for optimizing model adaptation for a speech recognition system
US20110029313A1 (en) * 2005-02-04 2011-02-03 Vocollect, Inc. Methods and systems for adapting a model for a speech recognition system
US7949533B2 (en) 2005-02-04 2011-05-24 Vococollect, Inc. Methods and systems for assessing and improving the performance of a speech recognition system
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US20140142943A1 (en) * 2012-11-22 2014-05-22 Fujitsu Limited Signal processing device, method for processing signal
US8914290B2 (en) 2011-05-20 2014-12-16 Vocollect, Inc. Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment
US9978395B2 (en) 2013-03-15 2018-05-22 Vocollect, Inc. Method and system for mitigating delay in receiving audio stream during production of sound from audio stream
CN111179939A (en) * 2020-04-13 2020-05-19 北京海天瑞声科技股份有限公司 Voice transcription method, voice transcription device and computer storage medium
WO2021134549A1 (en) * 2019-12-31 2021-07-08 李庆远 Human merging and training of multiple artificial intelligence outputs
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US8612235B2 (en) 2005-02-04 2013-12-17 Vocollect, Inc. Method and system for considering information about an expected response when performing speech recognition
US9202458B2 (en) 2005-02-04 2015-12-01 Vocollect, Inc. Methods and systems for adapting a model for a speech recognition system
US20070192101A1 (en) * 2005-02-04 2007-08-16 Keith Braho Methods and systems for optimizing model adaptation for a speech recognition system
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US8914290B2 (en) 2011-05-20 2014-12-16 Vocollect, Inc. Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment
US10685643B2 (en) 2011-05-20 2020-06-16 Vocollect, Inc. Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment
US11810545B2 (en) 2011-05-20 2023-11-07 Vocollect, Inc. Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment
US11817078B2 (en) 2011-05-20 2023-11-14 Vocollect, Inc. Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment
US20140142943A1 (en) * 2012-11-22 2014-05-22 Fujitsu Limited Signal processing device, method for processing signal
US9978395B2 (en) 2013-03-15 2018-05-22 Vocollect, Inc. Method and system for mitigating delay in receiving audio stream during production of sound from audio stream
US11837253B2 (en) 2016-07-27 2023-12-05 Vocollect, Inc. Distinguishing user speech from background speech in speech-dense environments
WO2021134549A1 (en) * 2019-12-31 2021-07-08 李庆远 Human merging and training of multiple artificial intelligence outputs
CN111179939A (en) * 2020-04-13 2020-05-19 北京海天瑞声科技股份有限公司 Voice transcription method, voice transcription device and computer storage medium
CN111179939B (en) * 2020-04-13 2020-07-28 北京海天瑞声科技股份有限公司 Voice transcription method, voice transcription device and computer storage medium

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JP2001100790A (en) 2001-04-13
DE50015670D1 (en) 2009-08-06

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